Variation in Episiotomy Use Among Nulliparous Individuals by Maternity Care Provider and Associated Rates of Obstetric Anal Sphincter Injury
Bibliographic record
Abstract
OBJECTIVES: To quantify variation in the association between episiotomy and obstetric anal sphincter injury (OASI) by maternity care provider in spontaneous and operative vaginal deliveries (SVDs and OVDs). METHODS: Population-based retrospective cohort study of vaginal, term deliveries among nullipara in Canada (2004-2015). Adjusted rate ratios (ARRs) and 95% CIs were estimated using log-binomial regression to quantify the associations between episiotomy and OASI, stratified by care provider (obstetrician [OB], family physician [FP], or registered midwife [RM]) while adjusting for potential confounders. RESULTS: The study included 631 642 deliveries. Episiotomy use varied by provider: among SVDs, the episiotomy rate was 19.6%, 14.4%, and 8.4% in the OB, FP, and RM groups, respectively. The rate of OASI was higher among SVDs with versus without episiotomy (5.8% vs 4.6%). Conversely, OASI occurred less frequently in operative vaginal deliveries with episiotomy (15.3%) compared with those without (16.7%). In all provider groups, the ARR for OASI was increased with episiotomy in SVD and decreased with episiotomy with forceps delivery. No differences in these associations were observed by provider except among vacuum delivery (ARR with episiotomy vs. without, OB: 0.88, 95% CI 0.84-0.92; FP: 0.89, 95% CI 0.83-0.96, RM: 1.22, 95% CI 1.02-1.48). CONCLUSIONS: In nullipara, irrespective of maternity care provider, there is a positive association between episiotomy and OASI among SVDs and an inverse association between episiotomy and deliveries with forceps. The relationship between episiotomy and OASI is modified by maternity care providers among vacuum deliveries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".